Research in the US has revealed how the brain organises memories into sequences and how this can be used to plan future behaviour.
The findings, from a team at the University of California, Irvine (UCI) could lead to understanding memory failures in cognitive disorders such as Alzheimer’s.
The researchers combined electrophysiological recording techniques in rodents with a statistical machine learning analysis of huge troves of data.
Their findings suggested that hippocampal network encodes and preserves the progressions of experiences to aid decision-making.
The research is published in the journal, Nature Communications.
Corresponding author Norbert Fortin, UCI associate professor of neurobiology and behaviour, said:
“Our brain keeps a pretty good record of when specific experiences or events occur. This ability helps us function in our daily life, but before this study, we didn’t have a clear idea of the neuronal mechanisms behind these processes.
“Where it connects with everybody is that this type of memory is strongly impaired in a variety of neurological disorders or simply with aging, so we really need to know how this brain function works.”
The researchers subjected rodents to a series of odour-identification tests and monitored the firing of the neurons in their brains.
By presenting five different smells in various sequences, the researchers could measure how well the animals remembered the sequence and detect how this was captured in their brains.
“The analogy I would think about is computing,” Fortin said.
“If I were to stick electrodes in your brain – we can’t; that’s why we use rats – I could see which cells are firing and which ones are not firing at any given moment.
“That provides us with some insight into how the brain represents and computes information.
“When we record activity patterns in a structure, it’s like we’re seeing zeros and ones in a computer.”
Having obtained neuronal activity and inactivity measurements in millisecond intervals over several minutes, Fortin said that he and his colleagues were in some ways able to ‘read the minds’ of their subjects by viewing the coding of the cells.
Statistical analysis of the findings was led by senior co-author Babak Shahbaba, UCI Chancellor’s Fellow and professor of statistics.
He noted that when neurons encode information such as memories, scientists can get a glimpse of that process by examining the pattern of spiking activity across all recorded neurons, known collectively as an ensemble.
Shahbaba said:
“We found that we could treat these neural patterns as images, and this unlocked our ability to apply deep machine learning methods.
“We analysed the data with a convolutional neural network, which is a methodology used frequently in image processing applications such as facial recognition.”
This way, the researchers were able to decode the firing of neurons to retrieve information.
Fortin added:
“We know what the signature for odour B looks like, just as we know the ones for A, C and D.
“Because of that, you can see when those signatures reappear at a different moment in time, such as when our subjects are anticipating something that has yet to happen.
“We’re seeing these signatures being quickly replayed as they’re thinking about the future.”